Hey friends,

While data scientist was rated as the sexiest job of the 21st century with:

• Rewarding career where you can make a great impact

• High pay job and great career prospect

I’ve seen many people who landed a data scientist role and suffered in their careers because of the misaligned expectations between what they thought they’d do and what they actually did in their jobs.

The worse thing that can happen is when you put in so much time and effort to become a data scientist, and it turns out that it’s not what you wanted that you end up wasting your time and energy.

In today’s issue, I’ll be sharing my top 5 reasons why you should not become a data scientist. I hope this list of reasons is helpful to you.

Let’s get started! 🚀

👀 Top 5 Reasons Not to Become a Data Scientist

By the way, my latest YouTube video is out to explain these 5 reasons. This is my 2nd video - let me know what you think! 💜

1. You don’t enjoy learning programming, statistics, or business

Data science is a multi-disciplinary career comprised of computer science (programming), math (statistics), and business domain knowledge.

If you don’t like coding or math, then you’ll be miserable every day.

If you don’t like or understand the business, then you’ll be miserable every day.

If you just want to focus on ONE thing and don’t want to learn other disciplines, then data science might not be the right career for you.

2. You only want to do Machine Learning

It’s easy to think that, as a data scientist, you’ll build machine learning models all day long and change the world like how ChatGPT does.

However, in reality, most business problems don’t actually need machine learning to be solved. Sometimes, all you need is just Excel, SQL queries or some data analytics to solve business problems.

If you think data scientists only build machine learning models, then you’ll get frustrated once you step into this field. Even worse, you’ll begin to hate your job because this is not what you expected.

The good news is that if you only want to do machine learning, then Machine Learning Engineer or AI Engineer role might be a better option for you as this is what the roles specialise in.

3. You don’t like to sell your solution to others

As a data scientist, being good at technical skills is just 50% of the game. The other 50% comes from having great communication skills, especially in data storytelling.

You can do the best data analytics or build the best ML models in the world, but if you can’t sell your solution to convince your stakeholders (or your boss) to take action, your solution (or insights) will go nowhere but only stay in the PowerPoint slides.

Sad, but true.

I still remember when I was a data scientist in my previous company, I couldn’t convince stakeholders to take action. They listened to my sharing, and that’s it. Nothing happened.

One day, when I was preparing my presentation slides to present in a meeting, a senior data scientist came and asked me,

I couldn’t understand what he meant at first. But after hearing how he did his presentation and managed to convince stakeholders all the time using stories, I began to realise the importance of storytelling.

That realisation itself is life-changing - because I finally knew how to sell my solution to others using storytelling.

4. You don’t like learning new things constantly

Tools and technology in data science keep changing every single day. The tools that you learn today might become obsolete next month.

Therefore, it’s very important to keep yourself updated by learning new tools or skills.

If you don’t like learning new things and keeping up with industry trends, then the data scientist role might not be your right choice.

Because data science is never about the destination where you can stop learning. Data science is about the learning journey where you get to learn new things, improve yourself, solve business problems using data, and have fun along the way.

5. You don’t like working with other people

Data science is a very collaborative work by nature.

If you’re someone who prefers to work in your own cubicle without talking to others, then data scientist might not be the best fit for you.

Because you’ll need to collaborate with product managers, data engineers, ML engineers and other data scientists.

TL;DR

Here are the 5 reasons why you should not become a data scientist:

• You don’t enjoy learning programming, statistics, or business

• You only want to do Machine Learning

• You don’t like to sell your solution to others

• You don’t like learning new things constantly

• You don’t like working with other people

Hopefully, you’ve learned more about data scientist role and see if it’s the career path that you want.

👉🏻 Over to you: Do you still want to become a data scientist after knowing these 5 reasons?

🚀 Whenever you’re ready, there are 4 ways I can help you:

1. Book a coaching call with me if you need help in the following:

2. Promote your brand to ~1000 subscribers in the data/tech space by sponsoring this newsletter.

3. Watch my YouTube videos where I talk about data science tips, programming, and my tech life (P.S. Don’t forget to like and subscribe 💜).

4. Follow me on LinkedIn and Twitter for more data science career insights, my mistakes and lessons learned from building a startup.

That's all for today

Thanks for reading. I hope you enjoyed today's issue. More than that, I hope it has helped you in some ways and brought you some peace of mind.

You can always write to me by simply replying to this newsletter and we can chat.

See you again next week.

- Admond